remove old protobuf eggs (#10473)

tools/mo/automation/package_BOM.txt

@@ -12,9 +12,6 @@ install_prerequisites/install_prerequisites_tf.bat
 install_prerequisites/install_prerequisites_tf.sh
 install_prerequisites/install_prerequisites_tf2.bat
 install_prerequisites/install_prerequisites_tf2.sh
-install_prerequisites/protobuf-3.6.1-py3.5-win-amd64.egg
-install_prerequisites/protobuf-3.6.1-py3.6-win-amd64.egg
-install_prerequisites/protobuf-3.6.1-py3.7-win-amd64.egg
 openvino/tools/mo/__init__.py
 openvino/tools/mo/__main__.py
 openvino/tools/mo/analysis/__init__.py

tools/mo/install_prerequisites/install_prerequisites.bat

@@ -176,11 +176,6 @@ IF %USE_VENV% == "true" (
     echo [ WARNING ] run install_prerequisites.bat "{caffe|tf|tf2|mxnet|kaldi|onnx}" venv
 )
 
-echo *****************************************************************************************
-echo Optional: To speed up model conversion process, install protobuf-*.egg located in the
-echo "model-optimizer\install_prerequisites" folder or building protobuf library from sources.
-echo For more information please refer to Model Optimizer FAQ, question #80.
-
 goto:eof
 
 :error

tools/mo/openvino/tools/mo/front/caffe/loader.py

@@ -94,11 +94,7 @@ def load_caffe_proto_model(caffe_pb2, proto_path: str, model_path: [str, None] =
                            'Run: set PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=cpp \n'
         except ImportError:
             # 3. cpp implementation is not available
-            message += 'However you can use the C++ protobuf implementation that is supplied with the OpenVINO toolkit ' \
-                       'or build protobuf library from sources. \n' \
-                       'Navigate to "install_prerequisites" folder and run: ' \
-                       'python -m easy_install protobuf-3.5.1-py($your_python_version)-win-amd64.egg \n' \
-                       'set PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=cpp'
+            message += 'Check that your protobuf package version is aligned with requirements_caffe.txt.'
         print(message + '\n\n' + refer_to_faq_msg(80))
 
     # Read proto layers